AI strategy and readiness assessment
Which AI workloads run in-house, and which stay with external providers.
Overview
Lindstead tells the board which AI workloads move in-house, which stay with external APIs, and in what order. The scope can use an existing assessment or include one where needed.
- ResultA board recommendation on use cases, hosting and the order of investment.
- InputAI plans, current systems and the decisions the board needs to make.
Key questions
- Which use cases involve data that must stay under our control?
- Where is an external API still the better choice?
- Are our data, skills and governance ready?
- What must the board decide now, and what can wait a year?
Approach
- AI readiness assessment AI use, data, skills, infrastructure and governance, checked against legal obligations.
- Workload classification Data sensitivity, regulation, volume and required capability decide where each use case runs.
- Board recommendation Options, the cost and risk of each, and a phased roadmap.
Deliverables
- Executive briefing Models, costs and regulation, in board language.
- Workload classification Each use case assigned to in-house, European cloud or API, with the reasons.
- Board recommendation and roadmap A decision paper with a phased plan, owners and review points.
Frequently asked questions
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It checks data, infrastructure, skills and governance against AI plans and the rules that apply. It shows which use cases can start now.
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Lindstead takes no commissions from vendors, cloud providers or model developers. Its fee does not depend on the choice. Every figure is sourced and dated.
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No. For many workloads an external API is the better choice.
Related
Discuss AI strategy with Lindstead.
A 30-minute meeting covers the use case, the requirements and a first plan.